Nurses’ roles and responsibilities in the provision of early palliative care: A grounded theory study.
Bibliographic record
Abstract
98 Background: The benefits of providing early palliative care (EPC) are well researched. Few studies have explored the knowledge and skill used by nurses to help patients and families transition to and receive palliative care. In this study, we examine the roles and responsibilities of nurses in the provision of EPC and explore some of the barriers and facilitators they encounter as part of this complicated work. Methods: We drew on constructivist grounded theory to guide our methods and analysis. Nurses were recruited from several ambulatory care clinics in a comprehensive cancer center in Ontario, Canada. Nurses who participated in the study completed semi-structured interviews seeking to examine the roles, responsibilities, knowledge, and skills they utilized to provide EPC. Results: Ten nurse practitioners, six staff nurses, and four advanced practice nurses completed interviews for a total of 20 participants. Participants practiced in a variety of settings such as head and neck, breast, pancreatic, and hematology. The core category Brokering Palliative Care includes three subcategories: (1) Moving backwards and forward – stepping back to assess patients’ willingness to hear about EPC and then proceeding by selling the benefits of palliative to improving everyday function; (2) Addressing misconceptions and stigma – dealing with patients’ assumptions about palliative care as diminishing hope and accelerating the end of life; and (3) Advocating with the interprofessional team – bringing patient concerns forward to the team, managing interprofessional dynamics, and seeding the process of referral to EPC. Conclusions: Oncology nurses play a central role by brokering EPC for patients with serious cancers and their families. They draw on their proximity to patients, relational and communication capabilities, care coordination skills, and advocacy abilities. Brokering palliative care is conditional on nurses’ comfort level, experience, workload, and relationships with other healthcare professionals, especially oncologists. Moreover, the brokering work of nurses must be enacted within the boundaries of the nursing role and their relative position within the healthcare system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".